mpmm_control | R Documentation |
mpmm
.mpmm_control
selects the numerical minimizer, method, associated
control parameters, parameter bounds, and likelihood estimation (REML or ML)
used by mpmm
.
mpmm_control(
optim = c("nlminb", "optim"),
method = c("BFGS", "L-BFGS-B"),
lower = NULL,
upper = NULL,
REML = FALSE,
profile = FALSE,
verbose = 2,
...
)
optim |
the numerical optimizer used in the fit |
method |
optimization method to be used - one of "BFGS" or "L-BFGS-B"
for bounded optimization (default |
lower |
a list of named parameter lower bounds, if NULL then built in
defaults are used when |
upper |
a list of named parameter upper bounds, if NULL then built in
defaults are used when |
REML |
logical; whether to use REML (TRUE) or maximum likelihood |
profile |
logical; option to improve speed and convergence by using REML parameter estimates as initial values for ML optimization |
verbose |
integer; report progress during minimization: 0 = silent; 1 = optimizer trace; 2 = parameter trace (default)) |
... |
control parameters for the chosen optimizer |
The optimizer used to minimize the objective function is
selected by the optim
argument. Additional control
parameters specific to the chosen optimizer are specified via the
dots argument. See nlminb
and optim
for available options. Adapted from S. Wotherspoon
https://github.com/SWotherspoon/RWalc/blob/master/R/RWalc.R
Returns a list with components
optim |
the name of the numerical optimizer as a string, "nlminb" or "optim" |
method |
optimization method to be used |
lower |
named list of lower parameter bounds |
upper |
named list of upper parameter bounds |
REML |
whether REML is to be used in place of ML |
profile |
whether to enhance convergence robustness |
verbose |
level of tracing information to be reported |
control |
list of control parameters for the optimizer |
nlminb
, optim
.
fit <- mpmm(~ ice + (ice | id),
data = ellie.ice.short,
control = mpmm_control(
optim = "nlminb",
REML = FALSE,
eval.max = 2000)
)
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